The regulation of gene expression dictates when, where, and to what degree protein isoforms are generated, thereby meeting the metabolic needs of various cell types that make up organs and living beings. Given the constantly changing microenvironment, this process is highly dynamic, capable of adjusting instantly to multiple external cues, or mounting gene expression responses within extended periods of time. To achieve diverse gene expression responses cells rely on multiple points of regulation that include modulating the origin and rate of transcription, altering pre-mRNA processing to induce the generation of alternatively spliced mRNA isoforms, changing the length or location of the 3' UTR through alternative polyadenylation, selective mRNA isoform translation, and altering the stability of mRNA pools. All of these gene expression steps are integrated and co-dependent. However, our understanding of the dynamic nature of gene expression is limited because most cell-based investigations analyze only steady-state levels of gene expression and because detailed analyses focus only on one of the multiple steps involved in representing a gene expression profile. This research application focuses on evaluating the dynamics of gene expression from pre-mRNA generation through RNA processing in the nucleus to translation and mRNA degradation in the cytoplasm with the long-term goal to chart the life span of all expressed mRNAs upon cellular transformation. We will test the hypothesis that alterations in the kinetics of gene expression steps set in stone unique gene expression programs that dictate cellular fate. Using novel metabolic labeling techniques we will track pre-mRNA dynamics in the nucleus (Aim 1) and mRNA dynamics in the cytoplasm (Aim 2) to develop a comprehensive understanding on the kinetic interplay that establishes steady-state gene expression patterns. Aim 3 will use this understanding and tools to determine to what degree alterations in the dynamics of gene expression steps contribute to the overall change in gene expression profiles that accompany Src-induced breast epithelial cell transformation. The experiments described will highlight how crucial the interplay between transcription, RNA processing and mRNA translation is for the development of altered gene expression programs. Furthermore, understanding the kinetics involved in establishing novel gene expression profiles may pave the way for novel therapies of human breast cancer. Throughout this project we will rely on our expertise in kinetics, RNA biology and bioinformatics to obtain complete kinetic profiles of gene expression unique to Src-induced breast epithelial cell transformation, thus producing a wealth of data useful to the gene expression and breast cancer research communities. The identification of breast cancer-specific gene expression events may be valuable for the development of novel early detection or prediction tools.